近似推理在水雷参数分析专家系统中的应用

为了尽快分析出未知水雷障碍参数,根据水雷战的特点,提出了建立未知水雷障碍参数分析专家系统的观点,对专家系统的设计方法进行了一定的探讨,并针对专家系统建立中的"瓶颈"问题,提出了基于Vague集插值近似推理的专家系统知识自动获取方法,在介绍推理过程的基础上给出了算例.从推理的结果来看,该方法具有较高的可信度,从而为专家系统的研制提供了一定的方法支持.     

基于在线学习的频谱感知次序策略*

认知无线电允许次级用户在频谱没有被主用户使用时动态地接入频谱进行数据传输。动态频谱接入是解决无线电频谱资源短缺和使用效率低下问题的有效方案,而频谱感知是实现动态频谱接入的关键挑战之一。次级用户的感知能力有限,为了快速找到频谱空闲概率最大的频段从而获得更多的频谱接入机会,研究了频谱感知次序问题。考虑到频谱空闲概率会随时间变化且对次级用户不可知,提出了一个在线学习框架,把频谱感知次序问题规约成经典多摇臂赌博机问题,并利用在线学习方法——满意折现汤普森抽样算法(satisficing discounted Thompson sampling)处理优化问题。仿真结果表明,和其他算法相比,所提算法可获得更多的频谱接入机会并且能够跟踪频谱空闲概率的变化。     

OFDM系统中深度神经网络指导的IQ不平衡补偿算法

正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)是现代移动通信中一项重要的物理层通信技术,并且OFDM系统要求子载波间严格正交。然而,在实际系统中,振荡器和滤波器等器件的非理想特性会导致同相正交(In-phase and Quadrature-phase,IQ)不平衡,从而破坏子载波的正交性,严重影响OFDM系统的性能。通过研究IQ不平衡对OFDM系统的影响,提出了一种并联深度神经网络架构下的IQ不平衡补偿算法。该算法利用了深度神经网络不依赖于模型的特点,直接从接收到的频域信号恢复原输入信号的二进制序列,并利用干扰信号来自镜像子载波的先验知识来初始化模型驱动的神经网络,加快其网络优化的收敛速度。仿真结果表明,该算法能有效地补偿IQ不平衡失真,并且在幅度和相位失真的补偿上,其性能都优于传统的基于导频的最小二乘补偿算法,证明了深度学习方法解决物理层问题的优越性。     

基于统一理论框架的故障诊断模型及学习进化方法

本文以概率图理论为基础，系统研究了基于这一理论框架的故障诊断模型，对模型的构建方法以及在不同场景下的模型演化方案进行了探讨，使得在统一理论框架下可实现多模式系统故障诊断、耦合故障诊断、动态故障诊断、故障预测等复杂情形的诊断。为了弥补单独利用基于模型的方法和基于数据的方法的缺陷，研究了诊断模型的学习进化策略，实现了诊断效果的改进和优化。另外，对模型后续的能力扩展和可能的研究方向进行了展望，为后续理论研究提供了参考。     

On the roles of free play in army exercises and the Russians

The article outlines the essential role of free play elements in various types of exercises for the development of in-depth and practical military professionalism. It thereafter argues why such use of free play contradicts the military science founded Russian Way of War.     

基于神经网络集成的传感器故障诊断研究

针对诊断传感器偏置故障及漂移故障的难点问题,提出了一种基于神经网络集成的传感器故障诊断方法。该方法将传感器输出看做时间序列,通过加噪声生成抖动数据,建立多组神经网络,以获得神经网络集成预测器输出。通过将预测器输出与传感器实际输出相比较获取残差序列,获得基于残差序列的传感器偏置故障和漂移故障的辨识策略,实现传感器故障在线诊断。应用结果表明该方法可以提高神经网络的运算精度,从而快速准确地检测和分离传感器故障,辨识传感器故障类型以及故障发生的时间。     

The Force Publique’s campaigns in the Congo-Arab War, 1892-1894

ABSTRACT

Between 1892 and 1894 the Force Publique of King Leopold II’s Congo Free State engaged in a series of little-known counter-insurgency operations against ivory and slave traders from Zanzibar, commonly referred to as Arabs. Without a particularly strong tradition of imperial service, this article argues that the predominantly Belgian officer corps borrowed and adapted methods used by more experienced colonial forces in the 19^th Century. Whether taken from existing literature or learned through experience, it reveals that the Force Publique’s counter-insurgency methods reflected many of the more recognisable aspects of traditional French and British approaches. It suggests that, despite the unique nature of each colonial campaign, basic principles could be adapted by whomsoever to overcome the military and political challenges of colonial conquest. The Force Publique’s campaigns in the Congo-Arab War, therefore, provide further evidence as to how some base theories could be universally applied.     

外语受蚀时间对语言学习策略使用频率的影响

调查外语受蚀时间对语言学习策略使用频率的影响。调查发现,学习者学习策略的使用频率,特别是记忆策略、认知策略和补偿策略的使用频率,随着受蚀时间的增加逐渐降低。     

Gabor-CNN for object detection based on small samples

Object detection models based on convolutional neural networks (CNN) have achieved state-of-the-art performance by heavily rely on large-scale training samples. They are insufficient when used in specific applications, such as the detection of military objects, as in these instances, a large number of samples is hard to obtain. In order to solve this problem, this paper proposes the use of Gabor-CNN for object detection based on a small number of samples. First of all, a feature extraction convolution kernel library composed of multi-shape Gabor and color Gabor is constructed, and the optimal Gabor convolution kernel group is obtained by means of training and screening, which is convolved with the input image to obtain feature information of objects with strong auxiliary function. Then, the k-means clustering algorithm is adopted to construct several different sizes of anchor boxes, which improves the quality of the regional proposals. We call this regional proposal process the Gabor-assisted Region Proposal Network (Gabor-assisted RPN). Finally, the Deeply-Utilized Feature Pyramid Network (DU-FPN) method is proposed to strengthen the feature expression of objects in the image. A bottom-up and a top-down feature pyramid is constructed in ResNet-50 and feature information of objects is deeply utilized through the transverse connection and integration of features at various scales. Experimental results show that the method proposed in this paper achieves better results than the state-of-art contrast models on data sets with small samples in terms of accuracy and recall rate, and thus has a strong application prospect.     

英语教学中的师生非语言交际行为

介绍了非语言交际行为的定义、分类及作用,重点分析了英语教学中师生非语言交际行为及手段,对比点评了师生非语言交际行为的文化差异,认为:作为语言交际行为的补充,非语言交际行为在语言教学中发挥着不可低估的作用.